Metallic objects, such as street light poles, in urban areas can become unintentionally electrically energized. Similarly, other conductive objects such as a fence around a playground or ball field can become electrified when nearby underground power cables have insulation degradation. A high contact voltage on such objects may pose a shock hazard to the public, especially where foot traffic is persistent. Causes of dangerous contact voltage include failure of wire insulation, improper electrical rework, and water ingress into fixture wiring.
Some public utilities address the public risk through periodic scanning of publicly-accessible areas to identify unintentionally energized objects. This is commonly accomplished by driving vehicles equipped with electric field sensors along public streets and thoroughfares in urban areas. The limitation to this approach is the necessity to have navigable roads that are near the contact voltage hazards. The potential exists for hazards that are beyond navigable roads, such as boat docks, marinas, fountains in retention ponds, urban parks, playgrounds, stadiums, community ballparks, and any area where floodwaters make thoroughfares impassible. Presently, detecting contact voltages at distances greater than approximately 30 feet away from a navigable roadway requires travel on foot and manual measurement.
A major challenge in identifying unintentionally energized objects is the ability to discern between such objects and the plethora of false positives caused by normal electric field sources, such as overhead power lines and above ground power cords. To address this challenge, a sensor is needed that can detect very weak electric fields at levels that are much lower than detectable using currently available commercial devices. A need also exists for algorithmic methods to combine electric and magnetic field information to identify a contact voltage source in proximity to normally energized objects.
What is needed, therefore, is a detection apparatus and suitable algorithms for detecting inadvertently energized sources by distinguishing between such unintentional sources and the plethora of normally expected electromagnetic sources in a real-world environment.